When we talk about the process of competitive intelligence, we imagine organizations taking the onus of cracking data insights from different primary and secondary sources to be put to use. Primary information is still tracked with the same old methods of interviews and help from Competitive Intelligence partners. But secondary research was very different in the earlier times when it was feasible for organizations to manually track relevant updates as the internet was not this messy and full from everyone putting out content. Now, we have moved quite forward in the internet age where most of the competitive and market intelligence can be found in the pool of information available on the internet but does a google search or google alerts update help you dive to the right core of this ocean is questionable.
So, let us learn the process of competitive intelligence step-by-step to understand the extraction of insights from Big data better.
Defining competitive intelligence for different roles
Competitive intelligence and insights can have subjective meaning for everyone. Different information is insightful for different roles. To understand what is an insight for a specific role, we need to relate the competitive intelligence with their end job role like the role of a salesperson is to generate leads, so the competitive insights of other companies changing their branding strategies are not very helpful to a salesperson who is not looking after brand management of the organization. They can surely forward the insights to the relevant teams but it makes much less sense for everyone to keep reading all the competitive intelligence even if it's not of their use.
Therefore, it is crucial to list down everything from relevant sources to leading competitors in the market matrix. This is the initial stage of the Competitive Intelligence process where you can limit your list to only significant competitors and sources but, in that process, you might also miss out on something important. All the stakeholders should be in sync with this step and take time and energy to filter the options available responsibly.
Secondary research
The next step is simply to stay updated on the important subjects from important sources including competitors, their websites, announcements, social media, market updates, etc. But is it that easy? Is it possible for stakeholders to exhaust their limited time in surfing the internet to find and track relevant competitive and market insights?
No, because the time spent on this activity would not be proportional to the quality of the content we get out of manual research. Even if a research analyst is hired for the same role, the quality of the updates cannot be promised from such a wide space of information with only human effort. The stakeholders might miss some information in this process which would mean a significant loss to the strategy of the organization as high-level strategic updates are of utmost value to only the first person who comes across that insight. Then, what is the solution to this challenge? AI-enabled market and competitive intelligence system mitigates these challenges by enhancing the quality of the updates delivered on time. Let's see how.
Artificial intelligence to Rescue
Artificial intelligence accelerates the process of gathering data and putting it to use. Moreover, an application of AI, Machine Learning extracts insights from Big Data by using algorithms to recognize patterns and trends. AI-enabled market and competitive intelligence solution eases the transition of information to insight by delivering only the personalized intelligence relevant to the stakeholder's role. The function of the MCI system is to automate competitive and market analysis.
When you are working with competitive intelligence, the significance is also boosted if you are the first in the market to be updated. There can be no second doubts on the fact that AI-enabled Market and Competitive Intelligence platform accelerates your competitive intelligence process and in turn, helps organizations build their competitive edge with time.
Conclusion
Even if an organization takes the decision of building its Competitive Intelligence platform, it is too tedious a process with too many challenges in the path. And in the end, the core product or service of the organization might suffer with so much allocation of time and resources to building a competitive intelligence platform. Hence, organizations prefer to leverage reliable competitive intelligence solutions. The reliability of a competitive intelligence platform is built upon two factors- first, the quality of updates it provides in a time-bound manner, and second, how well it works on the requirement of the stakeholder in collecting insights through data analysis.
Hence, AI-enabled market and competitive intelligence platform is a preferred choice for organizations to understand the competitive landscape, predict their rivals' movements, and decipher hidden market opportunities within a limited time.
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